Electronic device, estimation system, estimation method, and estimation program

ABSTRACT

An electronic device includes a sensor configured to acquire a pulse wave of a subject and a controller configured to analyze, based on the pulse wave of the subject acquired by the sensor, the rate of change in the pulse wave at a predetermined time after the point in time exhibiting a peak of the pulse wave and to estimate the blood glucose level of the subject based on the rate of change.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims priority to and the benefit of JapanesePatent Application No. 2018-044750 filed Mar. 12, 2018, the entirecontents of which are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to an electronic device, an estimationsystem, an estimation method, and an estimation program that estimate asubject's state of health from measured biological information.

BACKGROUND

Conventionally, a subject's (user's) state of health has been estimatedby measuring a blood component or measuring the blood fluidity. Thesemeasurements are made using a blood sample collected from the subject.An electronic device that measures biological information from the wristor other measured part of a subject is also known. For example, theelectronic device disclosed in patent literature (PTL) 1 measures asubject's pulse rate by being attached to the subject's wrist.

CITATION LIST Patent Literature

PTL 1: JP2002-360530A

SUMMARY

An electronic device according to an embodiment includes a sensorconfigured to acquire a pulse wave of a subject, and a controllerconfigured to analyze, based on the pulse wave of the subject acquiredby the sensor, a rate of change in the pulse wave at a predeterminedtime after a point in time exhibiting a peak of the pulse wave and toestimate a blood glucose level of the subject based on the rate ofchange.

An electronic device according to another embodiment includes a sensorconfigured to acquire a pulse wave of a subject, and a controllerconfigured to analyze, based on the pulse wave of the subject acquiredby the sensor, a rate of change in the pulse wave at a predeterminedtime after a point in time exhibiting a peak of the pulse wave and toestimate a lipid level of the subject based on the rate of change.

An estimation system according to an embodiment includes an electronicdevice and an information processing apparatus connected communicablywith each other. The electronic device includes a sensor configured toacquire a pulse wave of a subject. The information processing apparatusincludes a controller configured to analyze, based on the pulse wave ofthe subject acquired by the sensor, a rate of change in the pulse waveat a predetermined time after a point in time exhibiting a peak of thepulse wave and to estimate a blood glucose level of the subject based onthe rate of change.

An estimation system according to an embodiment includes an electronicdevice and an information processing apparatus connected communicablywith each other. The electronic device includes a sensor configured toacquire a pulse wave of a subject. The information processing apparatusincludes a controller configured to analyze, based on the pulse wave ofthe subject acquired by the sensor, a rate of change in the pulse waveat a predetermined time after a point in time exhibiting a peak of thepulse wave and to estimate a lipid level of the subject based on therate of change.

An estimation method according to an embodiment is an estimation methodto be executed by an electronic device. The estimation method includesacquiring a pulse wave of a subject; analyzing, based on the pulse waveof the subject, a rate of change in the pulse wave at a predeterminedtime after a point in time exhibiting a peak of the pulse wave; andestimating a blood glucose level of the subject based on the rate ofchange.

An estimation method according to an embodiment is an estimation methodto be executed by an electronic device. The estimation method includesacquiring a pulse wave of a subject; analyzing, based on the pulse waveof the subject, a rate of change in the pulse wave at a predeterminedtime after a point in time exhibiting a peak of the pulse wave; andestimating a lipid level of the subject based on the rate of change.

An estimation program according to an embodiment is for causing anelectronic device to execute the steps of acquiring a pulse wave of asubject; analyzing, based on the pulse wave of the subject, a rate ofchange in the pulse wave at a predetermined time after a point in timeexhibiting a peak of the pulse wave; and estimating a blood glucoselevel of the subject based on the rate of change.

An estimation program according to an embodiment is for causing anelectronic device to execute the steps of acquiring a pulse wave of asubject; analyzing, based on the pulse wave of the subject, a rate ofchange in the pulse wave at a predetermined time after a point in timeexhibiting a peak of the pulse wave; and estimating a lipid level of thesubject based on the rate of change.

BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings:

FIG. 1 illustrates the schematic configuration of an example of anelectronic device according to an embodiment;

FIG. 2 is a cross-section schematically illustrating the configurationof the electronic device of FIG. 1;

FIG. 3 illustrates an example of a usage state of the electronic devicein FIG. 1;

FIG. 4 is an external perspective view schematically illustrating anexample of an electronic device according to an embodiment;

FIG. 5 schematically illustrates a state in which the electronic deviceof FIG. 4 is worn;

FIG. 6 schematically illustrates an exterior portion and a sensor in afront view of the electronic device of FIG. 4;

FIG. 7 schematically illustrates the positional relationship between thewrist of the subject and a first arm of the sensor in a front view;

FIG. 8A schematically illustrates the positional relationship betweenthe wrist of the subject, the first arm of the sensor, and the exteriorportion of the measurement unit in a front view;

FIG. 8B schematically illustrates the positional relationship betweenthe wrist of the subject, the first arm of the sensor, and the exteriorportion of the measurement unit in a front view;

FIG. 9 is a functional block diagram of an electronic device;

FIG. 10 illustrates an example of an estimation method based on pulsewaves in an electronic device;

FIG. 11 illustrates an example of the acceleration pulse wave;

FIG. 12 illustrates an example of pulse waves acquired by a sensor;

FIG. 13A illustrates an example of an estimation method, based on achange in pulse waves, in an electronic device;

FIG. 13B illustrates another example of an estimation method, based on achange in pulse waves, in an electronic device;

FIG. 14 is a flowchart for deriving an estimation formula used by theelectronic device of FIG. 1;

FIG. 15 illustrates an example pulse wave;

FIG. 16 illustrates an example of the acceleration pulse wave;

FIG. 17 illustrates an example pulse wave;

FIG. 18A is a graph illustrating the preprandial pulse waveform in thepresent embodiment;

FIG. 18B is a graph illustrating the postprandial pulse waveform in thepresent embodiment;

FIG. 19 illustrates an example of neural network regression analysis;

FIG. 20 illustrates an example of neural network regression analysis;

FIG. 21A is a graph illustrating learning data for neural networkregression analysis;

FIG. 21B is a graph illustrating verification data for neural networkregression analysis;

FIG. 22 is a flowchart for estimating a subject's postprandial bloodglucose level using an estimation formula;

FIG. 23 is a flowchart for estimating a subject's postprandial bloodglucose level using a plurality of estimation formulas;

FIG. 24 is a flowchart for deriving an estimation formula used by anelectronic device according to a second embodiment;

FIG. 25 is a flowchart for estimating a subject's postprandial lipidlevel using the estimation formula derived with the flowchart in FIG.24;

FIG. 26 schematically illustrates the configuration of a systemaccording to an embodiment; and

FIG. 27 illustrates an example pulse wave.

DETAILED DESCRIPTION

The pain involved in collecting a blood sample prevents subjects fromestimating their own state of health routinely. Furthermore, anelectronic device that only measures pulse is unable to measure thesubject's state of health apart from the pulse. The present disclosuretherefore provides an electronic device, an estimation system, anestimation method, and an estimation program that can easily estimate asubject's state of health.

Embodiments are described below in detail with reference to thedrawings.

First Embodiment

FIG. 1 illustrates the schematic configuration of a first example of anelectronic device according to an embodiment. An electronic device 100of the first example illustrated in FIG. 1 includes a wearing portion110 and a measurement unit 120. FIG. 1 is a view of the electronicdevice 100 of the first example from a back face 120 a that conies intocontact with the measured part.

The electronic device 100 measures the subject's biological informationwhile the electronic device 100 is worn by the subject. The biologicalinformation measured by the electronic device 100 includes the subject'spulse wave. In an embodiment, the electronic device 100 of the firstexample may acquire the pulse wave while being worn on the subject'swrist.

In an embodiment, the wearing portion 110 is a straight, elongated hand.The pulse wave is, for example, measured in a state in which the subjecthas wrapped the wearing portion 110 of the electronic device 100 aroundthe wrist. In greater detail, the subject wraps the wearing portion 110around the wrist so that the back face 120 a of the measurement unit 120is in contact with the measured part and then measures the pulse wave.The electronic device 100 measures the pulse wave of blood flowingthrough the ulnar artery or the radial artery of the subject.

FIG. 2 is a cross-section of the electronic device 100 of the firstexample. FIG. 2 illustrates the measurement unit 120 and the wearingportion 110 around the measurement unit 120.

The measurement unit 120 includes the back face 120 a in contact withthe subject's wrist while worn and a front face 120 b opposite the backface 120 a. The measurement unit 120 includes an opening 111 on the backface 120 a side. A sensor 130 includes a first end that touches thesubject's wrist when the electronic device 100 of the first example isworn and a second end in contact with the measurement unit 120. In astate in which an elastic body 140 is not pressed, the first end of thesensor 130 protrudes from the opening 111 at the back face 120 a. Thefirst end of the sensor 130 includes a pulse pad 132. The first end ofthe sensor 130 is displaceable in a direction substantiallyperpendicular to the plane of the back face 120 a. The second end of thesensor 130 is in contact with the measurement unit 120 via a shaft 133.

The first end of the sensor 130 is in contact with the measurement unit120 via the elastic body 140. The first end of the sensor 130 isdisplaceable relative to the measurement unit 120. The elastic body 140includes a spring, for example. The elastic body 140 is not limited tobeing a spring and can be any other elastic body, such as resin or asponge. Instead of or along with the elastic body 140, a biasingmechanism such as a torsion coil spring may be provided on the rotationshaft 133 of the sensor 130, and the pulse pad 132 of the sensor 130 maybe placed in contact with the measured part that is subjected tomeasurement of the pulse wave of the subject's blood.

A controller, storage, communication interface, power source,notification interface, circuits for causing these components tooperate, cables for connecting these components, and the like may bedisposed in the measurement unit 120.

The sensor 130 includes an angular velocity sensor 131 that detectsdisplacement of the sensor 130. The angular velocity sensor 131 detectsthe angular displacement of the sensor 130. The type of sensor providedin the sensor 130 is not limited to the angular velocity sensor 131 andmay, for example, be an acceleration sensor, an angle sensor, anothermotion sensor, or a plurality of these sensors.

The electronic device 100 of the first example includes an inputinterface 141 on the front face 120 b of the measurement unit 120. Theinput interface 141 receives operation input from the subject and may beconfigured, for example, using operation buttons (operation keys). Theinput interface 141 may, for example, be configured by a touchscreen.

FIG. 3 illustrates an example of a usage state of the electronic device100 of the first example by the subject. The subject wraps theelectronic device 100 of the first example around the wrist for use. Theelectronic device 100 of the first example is worn in a state such thatthe back face 120 a of the measurement unit 120 is in contact with thewrist. With the electronic device 100 of the first example wrappedaround the wrist, the position of the measurement unit 120 can beadjusted so that the pulse pad 132 is in contact with the position ofthe ulnar artery or the radial artery.

In FIG. 3, while the electronic device 100 of the first example is worn,the first end of the sensor 130 is in contact with the skin above theradial artery, which is the artery on the thumb side of the subject'sleft hand. The first end of the sensor 130 is in contact with the skinabove the subject's radial artery as a result of the elastic force ofthe elastic body 140 arranged between the measurement unit 120 and thesensor 130. The sensor 130 is displaced in accordance with the movementof the subject's radial artery, i.e. pulsation. The angular velocitysensor 131 detects displacement of the sensor 130 and acquires the pulsewave. The pulse wave refers to a waveform representation of the temporalchange, acquired from the body surface, in volume of a blood vessel dueto inflow of blood.

Referring again to FIG. 2, in a state in which an elastic body 140 isnot pressed, the first end of the sensor 130 protrudes from the opening111. When the electronic device 100 of the first example is worn by thesubject, the first end of the sensor 130 is in contact with the skinabove the subject's radial artery, and in accordance with pulsation, theelastic body 140 expands and contracts, displacing the first end of thesensor 130. A component with an appropriate elastic modulus is used forthe elastic body 140 so as to expand and contract in accordance withpulsation without inhibiting pulsation. The opening width W of theopening 111 is greater than the vessel diameter, i.e.

the radial artery diameter in an embodiment. By the opening 111 beingprovided in the measurement unit 120, the back face 120 a of themeasurement unit 120 does not compress the radial artery when theelectronic device 100 of the first example is worn. Therefore, theelectronic device 100 of the first example can acquire a pulse wave withlittle noise, improving measurement accuracy.

FIG. 3 illustrates an example in which the electronic device 100 of thefirst example is worn on the wrist and acquires the pulse wave at theradial artery, but the electronic device 100 of the first example may,for example, acquire the pulse wave of blood flowing through a carotidartery at the subject's neck. In greater detail, the subject may pressthe pulse pad 132 lightly against the position of the carotid artery tomeasure the pulse wave. The subject may also wrap the electronic device100 of the first example around the neck so that the pulse pad 132 is atthe position of the carotid artery.

FIG. 4 is an external perspective view schematically illustrating asecond example of an electronic device according to an embodiment. Anelectronic device 100 of the second example illustrated in FIG. 4includes a wearing portion 210, a base 211, and a fixing portion 212 andmeasurement unit 220 attached to the base 211.

In the present embodiment, the base 211 is a substantially rectangularflat plate. In the present disclosure, the direction of the short sidesof the flat plate-shaped base 211 is considered the x-axis direction,the direction of the long sides of the flat plate-shaped base 211 isconsidered the y-axis direction, and the orthogonal direction of theflat plate-shaped base 211 is considered the z-axis direction, asillustrated in FIG. 4. A portion of the electronic device 100 of thesecond example is configured to be moveable, as described in the presentdisclosure. When describing the direction with regard to the electronicdevice 100 of the second example in the present disclosure, the x, y,and z-axis directions in the state in FIG. 4 are implied, unlessotherwise noted. In the present disclosure, the positive z-axisdirection is referred to as up, the negative z-axis direction as down,and the positive x-axis direction as the front of the electronic device100 of the second example.

The electronic device 100 of the second example measures the subject'sbiological information while the subject wears the electronic device 100of the second example using the wearing portion 210. The biologicalinformation measured by the electronic device 100 of the second exampleis the subject's pulse wave, which is measurable by the measurement unit220. As one example, the electronic device 100 of the second example isdescribed below as being worn on the subject's wrist and acquiring apulse wave.

FIG. 5 schematically illustrates a state in which a subject is wearingthe electronic device 100 of the second example in FIG. 4. The subjectcan wear the electronic device 100 as illustrated in FIG. 5 by insertinga wrist into the space formed by the wearing portion 210, the base 211,and the measurement unit 220 and fixing the wrist in place with thewearing portion 210. In the example illustrated in FIGS. 4 and 5, thesubject wears the electronic device 100 of the second example byinserting the wrist along the x-axis in the positive x-axis directionthrough the space formed by the wearing portion 210, the base 211, andthe measurement unit 220. The subject wears the electronic device 100 ofthe second example so that, for example, the pulse pad 132 of themeasurement unit 220, described below, is in contact with the positionof the ulnar artery or the radial artery. The electronic device 100 ofthe second example measures the pulse wave of blood flowing through theulnar artery or the radial artery at the subject's wrist.

The measurement unit 220 includes a body 221, an exterior portion 222,and a sensor 130. The sensor 130 is attached to the body 221. Themeasurement unit 220 is attached to the base 211 via a connectingportion 223.

The connecting portion 223 may be attached to the base 211 in arotatable manner along the surface of the base 211. In other words, inthe example in FIG. 4, the connecting portion 223 may be attached to thebase 211 in a rotatable manner in the xy plane relative to the base 211,as indicated by the arrow A. In this case, the entire measurement unit220 attached to the base 211 via the connecting portion 223 is rotatablein the xy plane relative to the base 211.

The exterior portion 222 is connected to the connecting portion 223along a shaft S1 that passes through the connecting portion 223. Theshaft S1 is a shaft extending in the x-axis direction. By the exteriorportion 222 being connected to the connecting portion 223 in this way,the exterior portion 222 is displaceable relative to the connectingportion 223 along a plane intersecting the xy plane along which the base211 extends. In other words, the exterior portion 222 can be inclinedabout the shaft S1 at a predetermined angle to the xy plane along whichthe base 211 extends. The exterior portion 222 can, for example, bedisplaced while positioned on a plane having a predetermined inclinationrelative to the xy plane, such as the yz plane. In the presentembodiment, the exterior portion 222 can be connected to the connectingportion 223 in a rotatable manner, in the yz plane orthogonal to the xyplane, about the shaft S1 as indicated by the arrow B in FIG. 4.

The exterior portion 222 includes a contact surface 222 a that comes incontact with the subject's wrist when the electronic device 100 of thesecond example is worn. The exterior portion 222 may include an opening225 on the contact surface 222 a side. The exterior portion 222 may beconfigured to cover the body 221.

The exterior portion 222 may include a shaft 224, extending in thez-axis direction, in an interior space. The body 221 includes a holethrough which the shaft 224 is passed. The body 221 is attached in theinterior space of the exterior portion 222 with the shaft 224 passedthrough the hole. In other words, the body 221 is attached to theexterior portion 222 in a rotatable manner, in the xy plane, about theshaft 224 relative to the exterior portion 222, as indicated by thearrow C in FIG. 4. The body 221 is thus attached to the exterior portion222 in a rotatable manner along the xy plane, which is the surface ofthe base 211, relative to the exterior portion 222. The body 221 is alsoattached to the exterior portion 222 in a displaceable manner in theup-down direction relative to the exterior portion 222, along the shaft224, i.e. along the z-axis direction, as indicated by the arrow D inFIG. 4.

The sensor 130 is attached to the body 221. Details of the sensor 130are described with reference to FIG. 6, which schematically illustratesthe exterior portion 222 and the sensor 130 in a front view of theelectronic device 100 of the second example. In FIG. 6, the portions ofthe sensor 130 that overlap with the exterior portion 222 in the frontview are indicated by dashed lines.

The sensor 130 includes a first arm 134 and a second arm 135. The secondarm 135 is fixed to the body 221. An end 135 a of the second arm 135 atthe lower side is connected to an end 134 a of the first arm 134. Thefirst arm 134 is connected to the second arm 135 so that the other end134 b is rotatable in the yz plane with the end 134 a as the axis ofrotation, as indicated by the arrow E in FIG. 6.

The other end 134 b of the first arm 134 is connected to the other end135 b of the second arm 135 at the upper side via the elastic body 140.The first arm 134 is supported by the second arm 135 in a state suchthat the first arm 134 is not being pressed by the elastic body 140, andthe other side 134 b of the sensor 130 is protruding from the opening225 of the exterior portion 222 towards the contact surface 222 a side.The elastic body 140 is, for example, a spring. The elastic body 140 isnot limited to being a spring, however, and can be any other elasticbody, such as resin or a sponge. Instead of or along with the elasticbody 140, a biasing mechanism such as a torsion coil spring may beprovided on a rotation shaft S2 of the first arm 134, and the pulse pad132 of the first arm 134 may be placed in contact with the measured partthat is subjected to measurement of the pulse wave of the subject'sblood.

The pulse pad 132 is connected to the other end 134 b of the first arm134. The pulse pad 132 is the portion placed in contact with themeasured part targeted for measurement of the pulse wave of thesubject's blood when the electronic device 100 of the second example isworn. In the present embodiment, the pulse pad 132 is, for example, incontact with the position of the ulnar artery or the radial artery. Thepulse pad 132 may be configured by a material that does not easilyabsorb changes in body surface due to the subject's pulse. The pulse pad132 may be configured by a material that is not painful for the user ina state of contact. For example, the pulse pad 132 may be formed by acloth bag filled with beads. The pulse pad 132 may, for example, beconfigured to be detachable from the first arm 134. The subject may, forexample, attach one pulse pad 132 to the first arm 134 from among aplurality of sizes and/or shapes of pulse pads 132 in accordance withthe size and/or shape of the subject's wrist. This enables the subjectto use the pulse pad 132 in accordance with the size and/or shape of thesubject's wrist.

The sensor 130 includes an angular velocity sensor 131 that detectsdisplacement of the first arm 134. It suffices for the angular velocitysensor 131 to be capable of detecting the angular displacement of thefirst arm 134. The type of sensor provided in the sensor 130 is notlimited to the angular velocity sensor 131 and may, for example, be anacceleration sensor, an angle sensor, another motion sensor, or aplurality of these sensors.

While the electronic device 100 of the second example is worn in thepresent embodiment, the pulse pad 132 is in contact with the skin abovethe radial artery, which is the artery on the thumb side of thesubject's right hand, as illustrated in FIG. 5. The elastic force of theelastic body 140 disposed between the second arm 135 and the first arm134 places the pulse pad 132 disposed at the other end 134 b of thefirst arm 134 in contact with the skin above the radial artery of thesubject. The first arm 134 is displaced in accordance with the movementof the subject's radial artery, i.e. pulsation. The angular velocitysensor 131 acquires the pulse wave by detecting displacement of thefirst arm 134. The pulse wave refers to a waveform representation of thetemporal change in volume of a blood vessel due to inflow of blood,acquired from the body surface.

As illustrated in FIG. 6, the other end 134 b of the first arm 134protrudes from the opening 225 while the elastic body 140 is not beingpressed. When the subject wears the electronic device 100, the pulse pad132 connected to the first arm 134 comes into contact with the skinabove the radial artery of the subject. The elastic body 140 expands andcontracts in accordance with pulsation, and the pulse pad 132 isdisplaced. A component with an appropriate elastic modulus is used forthe elastic body 140 so as to expand and contract in accordance withpulsation without inhibiting pulsation. The opening width W of theopening 225 is sufficiently greater than the vessel diameter, i.e. theradial artery diameter in the present embodiment. By the opening 225being provided in the exterior portion 222, the contact surface 222 a ofthe exterior portion 222 does not compress the radial artery when theelectronic device 100 of the second example is worn. Therefore, theelectronic device 100 of the second example can acquire a pulse wavewith little noise, improving measurement accuracy.

The fixing portion 212 is fixed to the base 211. The fixing portion 212may include a fixing mechanism for fixing the wearing portion 210. Eachfunctional component used for the electronic device 100 of the secondexample to measure the pulse wave may be included inside the wearingportion 210. For example, the fixing portion 212 may include thebelow-described input interface, controller, power source, storage,communication interface, notification interface, circuits for causingthese components to operate, cables for connecting these components, andthe like.

The wearing portion 210 is a mechanism used for fixing the subject'swrist to the electronic device 100 of the second example. In the exampleillustrated in FIG. 4, the wearing portion 210 is a straight, elongatedband. The wearing portion 210 in the example illustrated in FIG. 4 isarranged so that one end 210 a is connected to the upper end of themeasurement unit 220, the wearing portion 210 passes through the insideof the base 211, and another end 210 b is located in the positivedirection of the y-axis. For example, the subject inserts his rightwrist into the space formed by the wearing portion 210, the base 211,and the measurement unit 220 and pulls the other end 210 b of thewearing portion 210 in the positive direction of the y-axis with theleft hand while making adjustments so that the pulse pad 132 comes intocontact with the skin above the radial artery of the right wrist. Thesubject pulls the other end 210 b enough for the right wrist to be fixedto the electronic device 100 of the second example and fixes the wearingportion 210 in this state with the fixing mechanism of the fixingportion 212. In this way, the subject can put on the electronic device100 of the second example with one hand (the left hand in the presentembodiment). The subject can also use the wearing portion 210 to fix thewrist to the electronic device 100 of the second example, therebystabilizing the wearing state of the electronic device 100 of the secondexample. Consequently, the positional relationship between the wrist andthe electronic device 100 of the second example is less likely to changeduring measurement. This enables stable measurement of the pulse waveand improves measurement accuracy.

Next, movement of the moveable portion of the electronic device 100 ofthe second example at the time of wearing of the electronic device 100of the second example is described.

To wear the electronic device 100 of the second example, the subjectinserts the wrist along the x-axis direction into the space formed bythe wearing portion 210, the base 211, and the measurement unit 220, asdescribed above. The measurement unit 220 is configured to be rotatablein the direction of the arrow A of FIG. 4 relative to the base 211. Atthis time, the subject can therefore insert the wrist while rotating themeasurement unit 220 in the direction indicated by the arrow A of FIG.4. By the measurement unit 220 being configured in this way to berotatable, the subject can insert the wrist while appropriately changingthe direction of the measurement unit 220 in accordance with thepositional relationship between the subject and the electronic device100 of the second example. This makes it easier for the subject to wearthe electronic device 100 of the second example.

After inserting the wrist into the space formed by the wearing portion210, the base 211, and the measurement unit 220, the subject places thepulse pad 132 in contact with the skin above the radial artery of thewrist. The body 221 is configured to be displaceable in the direction ofthe arrow D of FIG. 4. The first arm 134 of the sensor 130 connected tothe body 221 is therefore also displaceable in the direction of thearrow D, which is the z-axis direction, as illustrated in FIG. 7.Therefore, the subject can displace the first arm 134 in the directionof the arrow D in accordance with the size, thickness, and the like ofthe subject's wrist so that the pulse pad 132 comes into contact withthe skin above the radial artery. The subject can fix the body 221 atthe position of displacement. The electronic device 100 of the secondexample thus facilitates adjustment of the position of the sensor 130 toa suitable position for measurement. The electronic device 100 of thesecond example thereby improves measurement accuracy. The body 221 hasbeen described as displaceable in the z-axis direction in the example inFIG. 4, but the body 221 is not necessarily configured to bedisplaceable in the z-axis direction. It suffices for the body 221 to beconfigured to be capable of adjusting the position in accordance withthe size, thickness, and the like of the wrist, for example. The body221 may, for example, be configured to be displaceable in a directionintersecting the xy plane, which is the surface of the base 211.

When the pulse pad 132 is in contact with the skin above the radialartery in a direction orthogonal to the skin surface, the pulsationtransmitted to the first arm 134 increases. In other words, when thedisplacement direction of the pulse pad 132 (the direction indicated bythe arrow E of FIG. 6) is a direction orthogonal to the skin surface,the pulsation transmitted to the first arm 134 increases, and theaccuracy with which pulsation is acquired can increase. In theelectronic device 100 of the second example, the body 221 and the sensor130 connected to the body 221 are configured to be rotatable about theshaft 224 with respect to the exterior portion 222, as indicated by thearrow C of FIG. 4. The subject can thereby adjust the direction of thesensor 130 so that the displacement direction of the pulse pad 132 is adirection orthogonal to the skin surface. In other words, the electronicdevice 100 of the second example enables adjustment of the direction ofthe sensor 130 so that the displacement direction of the pulse pad 132is a direction orthogonal to the skin surface. The electronic device 100of the second example thereby enables adjustment of the direction of thesensor 130 in accordance with the shape of the subject's wrist. Thisfacilitates transmission of a change in the pulsation of the subject tothe first arm 134. The electronic device 100 of the second examplethereby improves measurement accuracy.

The subject places the pulse pad 132 in contact with the skin above theradial artery of the wrist, as illustrated in FIG. 8A, and then pullsthe other end 210 b of the wearing portion 210 to fix the wrist to theelectronic device 100 of the second example. The exterior portion 222 isconfigured to be rotatable in the direction of the arrow B in FIG. 4.Therefore, when the subject pulls the wearing portion 210, the exteriorportion 222 rotates about the shaft S1, and the upper end is displacedin the negative direction of the y-axis. In other words, the upper endof the exterior portion 222 is displaced in the negative direction ofthe y-axis, as illustrated in FIG. 8B. The first arm 134 is connected tothe second arm 135 via the elastic body 140. Therefore, when the upperend of the exterior portion 222 is displaced in the negative directionof the y-axis, the pulse pad 132 is biased towards the radial artery bythe elastic force of the elastic body 140. Consequently, the pulse pad132 can more reliably capture changes in the pulse. The electronicdevice 100 of the second example thereby improves measurement accuracy.

The rotation direction of the exterior portion 222 (the directionindicated by arrow B) and the rotation direction of the first arm 134(the direction indicated by the arrow E) may be substantially parallel.As the rotation direction of the exterior portion 222 and the rotationdirection of the first arm 134 are closer to being parallel, the elasticforce of the elastic body 140 acts more efficiently on the first arm 134when the upper end of the exterior portion 222 is displaced in thenegative direction of the y-axis. The range over which the rotationdirection of the exterior portion 222 and the rotation direction of thefirst arm 134 are substantially parallel includes the range over whichthe elastic force of the elastic body 140 acts on the first arm 134 whenthe upper end of the exterior portion 222 is displaced in the negativedirection of the y-axis.

Here, the surface 222 b on the front side of the exterior portion 222illustrated in FIG. 8A is substantially rectangular, with the long sidesin the up-down direction. The surface 222 b includes a notch 222 c atthe upper end on the side in the negative direction of the y-axis. Thenotch 222 c makes the surface 222 b less likely to contact the skinabove the radial artery when the upper end of the exterior portion 222is displaced in the negative direction of the y-axis, as illustrated inFIG. 8B. This helps to prevent pulsation of the radial artery from beinghindered by contact with the surface 222 b.

Furthermore, when the upper end of the exterior portion 222 is displacedin the negative direction of the y-axis as illustrated in FIG. 8B, theend 222 d at the lower side of the notch 222 c contacts the wrist at adifferent position than the radial artery. When the end 222 d comes intocontact with the wrist, the exterior portion 222 is no longer displacedin the negative direction of the y-axis beyond the contact position. Theend 222 d can therefore prevent the exterior portion 222 from beingdisplaced beyond a predetermined position. If the exterior portion 222were displaced in the negative direction of the y-axis beyond apredetermined position, the first arm 134 would be strongly pressedtowards the radial artery by the elastic force of the elastic body 140.Pulsation of the radial artery would therefore tend to be hindered.Since the exterior portion 222 includes the end 222 d, the electronicdevice 100 of the second example can prevent an excessive pressure fromacting on the radial artery from the first arm 134, making the pulsationof the radial artery less likely to be hindered. In this way, the end222 d functions as a stopper that restricts the range over which theexterior portion 222 is displaceable.

In the present embodiment, the rotation shaft S2 of the first arm 134may be disposed at a position away from the side of the surface 222 b inthe negative direction of the y-axis, as illustrated in FIG. 8A. Whenthe rotation shaft S2 is disposed near the side of the surface 222 b inthe negative direction of the y-axis, the changes in pulsation of theradial artery might not be captured accurately due to the first arm 134touching the subject's wrist. The position of the rotation shaft S2 awayfrom the side of the surface 222 b in the negative direction of they-axis can reduce the probability of the first arm 134 touching thewrist, thereby making it easier for the first arm 134 to capture changesin pulsation more accurately.

The subject pulls the other end 210 b of the wearing portion 210 andfixes the wearing portion 210 with the fixing mechanism of the fixingportion 212 to wear the electronic device 100 of the second example onthe wrist. Once worn on the wrist in this way, the electronic device 100of the second example measures the subject's pulse wave by the first arm134 changing in the direction indicated by the arrow E together withchanges in pulsation.

The above-described first and second examples of the electronic device100 merely illustrate example configurations of the electronic device100. The electronic device 100 is therefore not limited to theconfigurations illustrated by the first and second examples. It sufficesfor the electronic device 100 to include a configuration capable ofmeasuring the subject's pulse wave.

FIG. 9 is a functional block diagram of the electronic device 100 of thefirst or second example. The electronic device 100 includes the sensor130, the input interface 141, a controller 143, a power source 144, astorage 145, a communication interface 146, and a notification interface147. In the electronic device 100 of the first example, the controller143, power source 144, storage 145, communication interface 146, andnotification interface 147 may be included inside the measurement unit120 or the wearing portion 110. In the electronic device 100 of thesecond example, the controller 143, power source 144, storage 145,communication interface 146, and notification interface 147 may beincluded inside the fixing portion 212.

The sensor 130 includes the angular velocity sensor 131, detectspulsation from the measured part, and acquires the pulse wave.

The controller 143 is a processor that, starting with the functionalblocks of the electronic device 100, controls and manages the electronicdevice 100 overall. Furthermore, the controller 143 is a processor that,using the acquired pulse wave, estimates the blood glucose level of thesubject. The controller 143 is configured by a processor, such as acentral processing unit (CPU), that executes programs prescribingcontrol procedures and programs for estimating the blood glucose levelof the subject. These programs may, for example, be stored on a storagemedium such as the storage 145. Based on an index calculated from thepulse wave, the controller 143 estimates a state related to thesubject's glucose metabolism, lipid metabolism, or the like. Thecontroller 143 may notify the notification interface 147 of data.

The power source 144 for example includes a lithium-ion battery and acontrol circuit for charging and discharging the battery. The powersource 144 supplies power to the electronic device 100 overall. Thepower source 144 is not limited to being a secondary cell such as alithium-ion battery and may, for example, be a primary cell such as abutton cell.

The storage 145 stores programs and data. The storage 145 may include anon-transitory storage medium, such as a semiconductor storage medium ora magnetic storage medium. The storage 145 may also include a pluralityof types of storage media. The storage 145 may include a combination ofa portable storage medium, such as a memory card, optical disc, ormagneto-optical disc, and an apparatus for reading the storage medium.The storage 145 may include a storage device used as a volatile storagearea, such as random access memory (RAM). The storage 145 stores avariety of information, programs for causing the electronic device 100to operate, and the like and also functions as a working memory. Thestorage 145 may, for example, store the measurement result of the pulsewave acquired by the sensor 130.

The communication interface 146 exchanges a variety of data with anexternal apparatus by wired or wireless communication. For example, thecommunication interface 146 communicates with an external apparatus thatstores the biological information of the subject to manage the state ofhealth. The communication interface 146 transmits, to the externalapparatus, the measurement result of the pulse wave measured by theelectronic device 100 and the state of health estimated by theelectronic device 100.

The notification interface 147 provides notification of information bysound, vibration, images, and the like. The notification interface 147may include a speaker, a vibration unit, and a display device. Thedisplay device can, for example, be a liquid crystal display (LCD), anorganic electro-luminescence display (OELD), an inorganicelectro-luminescence display (IELD), or the like. In an embodiment, thenotification interface 147 provides notification of the state of thesubject's glucose metabolism or lipid metabolism.

The electronic device 100 according to an embodiment estimates the stateof glucose metabolism. In an embodiment, the electronic device 100estimates the blood glucose level as the state of glucose metabolism.

The electronic device 100 estimates the subject's blood glucose levelbased on an estimation formula derived by regression analysis, forexample. The electronic device 100 stores the estimation formula forestimating the blood glucose level based on the pulse wave in thestorage 145, for example, in advance. The electronic device 100estimates the blood glucose level using this estimation formula.

Estimation theory related to estimating the blood glucose level based onthe pulse wave is now described. As a result of an increase in the bloodglucose level after a meal, the blood fluidity reduces (viscosityincreases), blood vessels dilate, and the amount of circulating bloodincreases. Vascular dynamics and hemodynamics are determined so as tobalance these states. The reduction in blood fluidity occurs, forexample, because of an increase in the viscosity of blood plasma or areduction in the deformability of red blood cells. Dilation of bloodvessels occurs for reasons such as secretion of insulin, secretion ofdigestive hormones, and a rise in body temperature. When blood vesselsdilate, the pulse rate increases to suppress a reduction in bloodpressure. Furthermore, the increase in the amount of circulating bloodcompensates for blood consumption for digestion and absorption. Thepostprandial vascular dynamics and hemodynamics due to these causes arealso reflected in the pulse wave. The electronic device 100 cantherefore estimate the blood glucose level based on the pulse wave.

An estimation formula for estimating the blood glucose level based onthe above estimation theory can be derived by performing regressionanalysis on sample data of postprandial pulse waves and blood glucoselevels obtained from a plurality of subjects. By applying the derivedestimation formula to the index in accordance with the subject's pulsewave at the time of estimation, the subject's blood glucose level can beestimated. If the estimation formula is derived in particular byperforming regression analysis using sample data for which variation inthe blood glucose level is close to a normal distribution, the bloodglucose level of the subject being tested can be estimated. Theestimation formula may, for example, be derived by partial least squares(PLS) regression analysis. In PLS regression analysis, a regressioncoefficient matrix is calculated by using the covariance of the outcomevariable (feature amount of the estimation target) and the explanatoryvariable (feature amount used for estimation) to perform multipleregression analysis by adding to the variable in order from thecomponent with the highest correlation between the outcome variable andthe explanatory variable.

“Preprandial” as used in the present disclosure refers to before a mealis taken, such as when fasting. “Postprandial” as used in the presentdisclosure refers to a time after a meal is taken, such as the time whenthe effects of the meal are reflected in the blood at a predeterminedtime after the meal is taken. As described in the present embodiment,“postprandial” in the case of the electronic device 100 estimating theblood glucose level may refer to the time at which the blood glucoselevel increases (for example, approximately one hour after the start ofthe meal).

FIG. 10 illustrates an example pulse wave to illustrate an example of anestimation method based on pulse waves. The estimation formula forestimating blood glucose level is, for example, derived by regressionanalysis related to age, an index SI indicating the rising of a pulsewave (rising index), an augmentation index (AI), and pulse rate PR.

The rising index SI is derived in accordance with the waveform indicatedin the area D1 of FIG. 10. In greater detail, the rising index SI is theratio of the first local minimum to the first local maximum in theacceleration pulse wave yielded by the second derivative of the pulsewave. For example, for the acceleration pulse wave illustrated as anexample in FIG. 11, the rising index SI is expressed as b/a. The risingindex SI decreases because of a reduction in fluidity of the blood,secretion of insulin, dilation (relaxation) of blood vessels due toincreased body temperature, and the like after a meal. In theacceleration pulse wave b/a, b is negative, and a is positive. In thiscase, b/a is negative. A smaller value of b/a means that b is growing inthe negative direction.

The AI is an index represented by the ratio between the magnitudes ofthe forward wave and the reflected wave of the pulse wave. A method ofderiving AI is described with reference to FIG. 12, which illustrates anexample of pulse waves acquired at the wrist using the electronic device100. FIG. 12 illustrates the case of using the angular velocity sensor131 as means for detecting the pulsation. FIG. 12 is a time integrationof the angular velocity acquired by the angular velocity sensor 131,with the horizontal axis representing time and the vertical axisrepresenting the angle. Since the acquired pulse wave may, for example,include noise that is due to body movement of the subject, the pulsewave may be corrected by a filter that removes the direct current (DC)component, so as to extract only the pulsation component.

Propagation of the pulse wave is a phenomenon in which pulsation due toblood extruded from the heart is transmitted through artery walls orblood. The pulsation due to blood pumped from the heart reaches theperipheries of limbs as a forward wave, a portion of which is reflectedat locations such as where a blood vessel branches, or where thediameter of a blood vessel changes, and returns as a reflected wave. AIis the quotient when the magnitude of the reflected wave is divided bythe magnitude of the forward wave and is expressed asAin=(PRn−PSn)/(PFn−PSn). Here, AIn is the AI for each pulse beat. AImay, for example, be calculated by measuring the pulse wave for severalseconds and calculating the average AIave of the AIn for each pulse beat(n=an integer from 1 to n). The AI is derived from the waveformindicated in area D2 of FIG. 10. The AI reduces because of a reductionin fluidity of the blood, dilation of blood vessels due to increasedbody temperature, and the like after a meal.

The pulse rate PR is derived from the period TPR of the pulse waveillustrated in FIG. 10. The pulse rate PR rises after a meal.

The electronic device 100 can estimate the blood glucose level using theestimation formula derived from the rising index SI, the AI, and thepulse rate PR.

FIGS. 13A and 13B illustrate another example of an estimation methodbased on pulse waves. FIG. 13A illustrates a pulse wave, and FIG. 13Billustrates the result of performing a fast Fourier transform (FFT) onthe pulse wave of FIG. 13A. The estimation formula for estimating theblood glucose level is, for example, derived by regression analysisrelated to a fundamental and harmonic component (Fourier coefficients)that are derived by an FFT. The peak value in the result of the FFTillustrated in FIG. 13B changes in accordance with change in thewaveform of the pulse wave. Therefore, the blood glucose level can beestimated with an estimation formula derived using the Fouriercoefficients.

Based on the above-described rising index SI, AI, pulse rate PR, Fouriercoefficients, and the like, the electronic device 100 uses theestimation formula to estimate the blood glucose level of the subject.

Here, a method for deriving an estimation formula for the case of theelectronic device 100 estimating the subject's blood glucose level isdescribed. The estimation formula need not be derived by the electronicdevice 100 and may be derived in advance using another computer or thelike. In the present disclosure, the device that derives the estimationformula is referred to as an estimation formula derivation apparatus.The derived estimation formula is, for example, stored in the storage145 in advance, before the subject estimates the blood glucose levelwith the electronic device 100.

FIG. 14 is a flowchart for deriving an estimation formula used by theelectronic device 100. The estimation formula is derived by performingregression analysis based on sample data obtained by measuring asubject's postprandial pulse wave using a pulse wave meter and measuringthe subject's postprandial blood glucose level using a blood glucosemeter. The acquired sample data are not limited to after a meal. Itsuffices to use data for time slots with large variation in the bloodglucose level.

During derivation of the estimation formula, first, information relatedto the subject's postprandial pulse wave, as measured by a pulse wavemeter, is inputted into the estimation formula derivation apparatus(step S101).

Information related to the subject's postprandial blood glucose level,as measured by a blood glucose meter, is also inputted into theestimation formula derivation apparatus (step S102). The blood glucoselevel inputted in step S102 is, for example, measured with a bloodglucose meter by taking a blood sample. The age of the subject for eachset of sample data may also be inputted in step S101 or step S102.

The estimation formula derivation apparatus determines whether thenumber of samples in the sample data inputted in step S101 and step S102is N or greater, which is an amount sufficient for regression analysis(step S103). The sample number N can be determined appropriately and canbe 100, for example. When determining that the number of samples is lessthan N (No), the estimation formula derivation apparatus repeats stepS101 and step S102 until the number of samples becomes N or greater.Conversely, when determining that the number of samples is N or greater(Yes), the estimation formula derivation apparatus proceeds to step S104and calculates the estimation formula.

During calculation of the estimation formula, the estimation formuladerivation apparatus analyzes the inputted postprandial pulse wave (stepS104). For example, the estimation formula derivation apparatus analyzesthe rising index SI, the AI, and the pulse rate PR of the postprandialpulse wave. The estimation formula derivation apparatus may analyze thepulse wave by performing FFT analysis.

The estimation formula derivation apparatus then performs regressionanalysis (step S105). The outcome variable in the regression analysis isthe postprandial blood glucose level. The explanatory variables in theregression analysis are, for example, the age inputted in step S101 orstep S102 and the rising index SI, the AI, and the pulse rate PR of thepostprandial pulse wave analyzed in step S104. When the estimationformula derivation apparatus performs FFT analysis in step S104, theexplanatory variables may, for example, be Fourier coefficientscalculated as the result of the FFT analysis.

The estimation formula derivation apparatus derives an estimationformula for estimating the postprandial blood glucose level based on theresult of regression analysis (step S106).

Depending on the waveform of the pulse wave, the AI may be difficult todetect. FIG. 15 illustrates an example pulse wave. The pulse waveillustrated in FIG. 15 is greatly affected by the reflected wave,represented by the second peak. FIG. 16 illustrates the accelerationpulse wave of the pulse wave illustrated in FIG. 15. The effect of thereflected wave also appears in the waveform of the acceleration pulsewave, as illustrated in FIG. 16, for example. When AI becomes small, AImay be difficult to detect or may disappear and be undetectable.Examples of when AI becomes small are when blood vessels dilate or theblood glucose level is high.

Therefore, instead of or in addition to the AI, the estimation formulamay be derived using another index. The use of another index AIt is nowdescribed as an example. AIt is the rate of change in the pulse wave ata predetermined time after the peak of the pulse wave. FIG. 17illustrates an example pulse wave to illustrate the AIt. The AIt is theratio of P3 to P1, where P1 is the height of the peak of the pulse wave,and P3 is the height of the pulse wave after a predetermined time Δtfrom the point in time when P1 appears. In other words, AIt=P3/P1. Thepredetermined time Δt may be a time before the effect of the reflectedwave appears. For example, if the pulse wave velocity is 10 m/sec, andthe distance from the heart to the main reflection point inside the bodyis 1 m round trip, then the time until the reflected wave makes a roundtrip is 100 msec. The predetermined time Δt may, for example, be 100msec calculated in this way. In other words, suppose the main reflectionpoint of the reflected wave of AI is the abdominal aortic bifurcation.Also suppose that the round-trip distance between the heart and theabdominal aortic bifurcation is 2L, and the pulse wave velocity is PWV.This yields Δt=2L/PWV. The pulse wave velocity of the abdominal aorta isgenerally thought to be 10 m/sec. The value of L is generally 50 cm.Accordingly, Δt=2L/PWV=100/1000=0.1 sec.

Naturally, the predetermined time Δt may vary depending on individualdifferences in the round-trip distance 2L and the pulse wave velocityPWV, the measurement time, the state of health, or other factors. Forexample, the round-trip distance 2L and the pulse wave velocity PWV mayvary from the aforementioned example values due to age, sex, healthstatus, or other factors. The predetermined time Δt may therefore varyfrom 100 msec and may be a numerical value in a certain range. Forexample, the predetermined time Δt may be 100 msec or less, or 100 msecor more. Setting the predetermined time Δt in this way facilitatesaccurate calculation of the AIt even when the reflected wave disappears.Depending on the waveform of the pulse wave, the use of AIt as an indexrelated to pulse wave can improve the estimation accuracy of thesubject's blood glucose level as compared to when AI is used. Thepredetermined time Δt is the time around which the reflected waveappears. The effect of the reflected wave is often included in the AIt.

With reference to FIGS. 18A and 18B, the change from the preprandialpulse waveform to the postprandial pulse waveform is now described.FIGS. 18A and 18B are graphs illustrating the change from thepreprandial pulse waveform to the postprandial pulse waveform in thepresent embodiment. In FIGS. 18A and 18B, the horizontal axis representstime, and the vertical axis represents the pulse wave. FIG. 18A is thepreprandial pulse waveform, and FIG. 18B is the pulse waveform one hourafter a meal. Both pulse waveforms are for the pulse wave of the sameindividual. As illustrated in FIG. 18B, the postprandial AI may becomesmall and difficult to detect. As the blood glucose level increases, AIfurther decreases or disappears.

The estimation formula derivation apparatus can derive an estimationformula with the flowchart described with reference to FIG. 14, usingthe AIt as one explanatory variable. In the present embodiment, theestimation formula derivation apparatus is described below as derivingan estimation formula with the above-described age, rising index SI, AI,pulse rate PR, and also AIt as explanatory variables.

The estimation formula is not necessarily derived by PLS regressionanalysis. The estimation formula may be derived using another method.For example, the estimation formula may be derived by neural networkregression analysis.

FIG. 19 illustrates an example of neural network regression analysis.FIG. 19 schematically illustrates a neural network in which the inputlayer is five neurons and the output layer is one neuron. The fiveneurons of the input layer are age, rising index SI, AI, AIt, and pulserate PR. The neuron of the output layer is the blood glucose level. Theneural network illustrated in FIG. 19 includes five intermediate layersbetween the input layer and the output layer: intermediate layer 1,intermediate layer 2, intermediate layer 3, intermediate layer 4, andintermediate layer 5. Intermediate layer 1 has 5 nodes, intermediatelayer 2 has 4 nodes, intermediate layer 3 has 3 nodes, intermediatelayer 4 has 2 nodes, and intermediate layer 5 has 1 node. Each node ofthe intermediate layers receives input of the sum of components of datathat are outputted from the preceding layer and weighted. Each node ofthe intermediate layers outputs a value yielded by performing apredetermined calculation (bias) on the inputted data. During neuralnetwork regression analysis, backpropagation is used to compare theestimated output value with the correct output value, and the weightingand bias are adjusted in the network to minimize the difference betweenthese two values. The estimation formula can be derived in this way byneural network regression analysis.

The neural network regression analysis used in the present embodiment isnot limited to the case illustrated in FIG. 19. For example, the exampleof neural network regression analysis illustrated in FIG. 20 may beused. In FIG. 20, the four neurons of the input layer are age, pulserate PR, AI, and AIt. The neuron of the output layer is the bloodglucose level.

FIGS. 21A and 21B illustrate the learning data and verification dataused in the neural network regression analysis of the present embodimentillustrated in FIG. 19. FIG. 21A is a graph illustrating learning datafor the neural network regression analysis of the present embodiment,and FIG. 21B is a graph illustrating verification data for neuralnetwork regression analysis.

Next, an example process for estimating the subject's blood glucoselevel using an estimation formula is described. FIG. 22 is a flowchartfor estimating a subject's postprandial blood glucose level using thederived estimation formula.

First, the electronic device 100 receives input of the subject's agebased on operation of the input interface 141 by the subject (stepS201).

After the subject eats a meal, the electronic device 100 measures thesubject's postprandial pulse wave based on operation by the subject(step S202).

The electronic device 100 then analyzes the measured postprandial pulsewave (step S203). For example, the electronic device 100 analyzes therising index SI, the AI, the AIt, and the pulse rate PR related to themeasured postprandial pulse wave.

The electronic device 100 applies the subject's age received as input instep S201 and the rising index SI, the AI, the AIt, and the pulse ratePR analyzed in step S203 to the estimation formula and estimates thesubject's postprandial blood glucose level (step S204). The subject isnotified of the estimated postprandial blood glucose level by thenotification interface 147 of the electronic device 100, for example.

In this way, the electronic device 100 according to the presentembodiment uses an estimation formula derived based on the postprandialpulse wave and blood glucose level to estimate the subject'spostprandial blood glucose level based on the subject's measuredpostprandial pulse wave. The electronic device 100 can thereforeestimate the postprandial blood glucose level rapidly and in anon-invasive manner. Consequently, the electronic device 100 can easilyestimate the subject's state of health.

As an index related to pulse wave, the AIt is not affected by thedisappearance of the reflected wave as compared to the AI. Use of theAIt, therefore, can improve the estimation accuracy of the subject'sblood glucose level. Even when the reflected wave AI is difficult todetect, the AIt can be detected stably, thereby improving accuracy.

The electronic device 100 is not limited to the postprandial bloodglucose level and may estimate the subject's blood glucose level at anytiming. The electronic device 100 can also estimate the blood glucoselevel at any timing rapidly and in a non-invasive manner.

The method of estimating the postprandial blood glucose level by theelectronic device 100 is not limited to the above-described method. Forexample, each time the electronic device 100 estimates the subject'spostprandial blood glucose level, the electronic device 100 may selectone estimation formula from among a plurality of estimation formulas andestimate the subject's postprandial blood glucose level using theselected estimation formula. A plurality of estimation formulas arederived in advance in this case.

A plurality of estimation formulas may, for example, be derived inaccordance with the content of meals. The content of a meal may, forexample, include the quantity and quality of the meal. The quantity ofthe meal may, for example, include the weight of the meal. The qualityof the meal may, for example, include the menu item, ingredients (food),cooking method, or the like.

The content of the meal may, for example, be classified into a pluralityof categories. The content of the meal may, for example, be classifiedinto the categories of noodles, set meals, bowls, or the like. The samenumber of estimation formulas as the number of categories of the contentof a meal may, for example, be derived. In other words, when the contentof the meal is classified into three categories, an estimation formulamay be derived in association with each category. In this case, thenumber of derived estimation formulas is three. The electronic device100 uses the estimation formula, among the plurality of estimationformulas, corresponding to the content of the subject's meal to estimatethe postprandial blood glucose level.

An example process for estimating the subject's blood glucose levelusing an estimation formula in the case of a plurality of derivedestimation formulas is now described. FIG. 23 is a flowchart forestimating a subject's postprandial blood glucose level using aplurality of derived estimation formulas.

The electronic device 100 receives input of the subject's age based onoperation of the input interface 141 by the subject (step S301).

The electronic device 100 receives input of the content of the mealbased on operation of the input interface 141 by the subject (stepS302). The electronic device 100 can receive input of the content of themeal from the subject by various methods. For example, when theelectronic device 100 includes a display device, the electronic device100 may receive input by displaying contents of meals (for example,categories) in a manner selectable by the subject and prompting thesubject to select the content of the meal closest to the meal thesubject is about to eat. The electronic device 100 may, for example,receive input by having the subject list the content of the meal usingthe input interface 141. When the electronic device 100 includes animaging unit such as a camera, the electronic device 100 may, forexample, receive input by using the imaging unit to capture an image ofthe meal about to be eaten. In this case, the electronic device 100 may,for example, estimate the content of the meal by image analysis on thecaptured image that is received.

The electronic device 100 measures the subject's postprandial pulse wavebased on operation by the subject (step S303).

The electronic device 100 analyzes the measured pulse wave (step S304).For example, the electronic device 100 analyzes the rising index SI, theAI, the AIt, and the pulse rate PR related to the measured pulse wave.

The electronic device 100 selects one estimation formula from among theplurality of estimation formulas based on the meal content received instep S302 (step S305). For example, the electronic device 100 selectsthe estimation formula associated with the category closest to theinputted content of the meal.

The electronic device 100 applies the subject's age received as input instep S301 and the rising index SI, the AI, the AIt, and the pulse ratePR analyzed in step S304 to the estimation formula and estimates thesubject's postprandial blood glucose level (step S306). The subject isnotified of the estimated postprandial blood glucose level by thenotification interface 147 of the electronic device 100, for example.

The postprandial blood glucose level may change depending on the contentof the meal. Nevertheless, the electronic device 100 can estimate theblood glucose level more accurately in accordance with the content ofthe meal by estimating the postprandial blood glucose level using anestimation formula, among a plurality of estimation formulas, thatcorresponds to the content of the meal.

Second Embodiment

In the first embodiment, the case of the electronic device 100estimating the subject's postprandial blood glucose level has beendescribed. In the second embodiment, an example of the electronic device100 estimating the subject's postprandial lipid level is described.Here, the lipid level includes neutral lipids, total cholesterol, HDLcholesterol, LDL cholesterol, and the like. In the description of thepresent embodiment, a description of points that are similar to thefirst embodiment is omitted as appropriate.

The electronic device 100 stores estimation formulas for estimating thelipid level based on the pulse wave in the storage 145, for example, inadvance. The electronic device 100 estimates the lipid level using theseestimation formulas.

The estimation theory related to estimating the lipid level based onpulse wave is similar to the estimation theory for blood glucose leveldescribed in the first embodiment. In other words, a change in the lipidlevel of the blood is also reflected in the waveform of the pulse wave.Therefore, the electronic device 100 can acquire the pulse wave andestimate the lipid level based on the acquired pulse wave.

FIG. 24 is a flowchart for deriving an estimation formula used by theelectronic device 100 according to the present embodiment. In thepresent embodiment as well, the estimation formula is derived byperforming regression analysis, such as PLS regression analysis orneural network regression analysis, based on sample data. In the presentembodiment, the estimation formula is derived based on the postprandialpulse wave as the sample data. “Postprandial” as used in the presentembodiment may refer to a time when the lipid level is higher at apredetermined time after a meal is taken (for example, approximatelythree hours after the start of a meal). If the estimation formula isderived in particular by performing regression analysis using sampledata for which variation in the lipid level is close to a normaldistribution, the lipid level at any timing can be estimated for thesubject being tested.

During derivation of the estimation formula, first, information relatedto the subject's postprandial pulse wave, as measured by a pulse wavemeter, is inputted into the estimation formula derivation apparatus(step S401).

Information related to the subject's postprandial lipid level, asmeasured by a lipid measurement apparatus, is also inputted into theestimation formula derivation apparatus (step S402). The age of thesubject for each set of sample data may also be inputted in steps S401and S402.

The estimation formula derivation apparatus determines whether thenumber of samples in the sample data inputted in step S401 and step S402is N or greater, which is an amount sufficient for regression analysis(step S403). The sample number N can be determined appropriately and canbe 100, for example. When determining that the number of samples is lessthan N (No), the estimation formula derivation apparatus repeats stepS401 and step S402 until the number of samples becomes N or greater.Conversely, when determining that the number of samples is N or greater(Yes), the estimation formula derivation apparatus proceeds to step S404and calculates the estimation formula.

During calculation of the estimation formula, the estimation formuladerivation apparatus analyzes the inputted postprandial pulse wave (stepS404). In the present embodiment, the estimation formula derivationapparatus analyzes the rising index SI, the AI, the AIt, and the pulserate PR of the postprandial pulse wave. The estimation formuladerivation apparatus may analyze the pulse wave by performing FFTanalysis.

The estimation formula derivation apparatus then performs regressionanalysis (step S405). The outcome variable in the regression analysis isthe postprandial lipid level. The explanatory variables in theregression analysis are, for example, the age inputted in step S401 orstep S402 and the rising index SI, the AI, the AIt, and the pulse ratePR of the postprandial pulse wave analyzed in step S404. When theestimation formula derivation apparatus performs FFT analysis in stepS404, the explanatory variables may, for example, be Fouriercoefficients calculated as the result of the FFT analysis.

The estimation formula derivation apparatus derives an estimationformula for estimating the postprandial lipid level based on the resultof regression analysis (step S406).

Next, the process for estimating the subject's lipid level using anestimation formula is described. FIG. 25 is a flowchart for estimating asubject's postprandial lipid level using the estimation formula derivedwith the flowchart in FIG, 24, for example.

First, the electronic device 100 receives input of the subject's age inresponse to operation of the input interface 141 by the subject (stepS501).

The electronic device 100 also measures the subject's postprandial pulsewave based on operation by the subject (step S502).

Next, the electronic device 100 analyzes the measured pulse wave (stepS503). For example, the electronic device 100 analyzes the rising indexSI, the AI, the Alt, and the pulse rate PR related to the measured pulsewave.

The electronic device 100 estimates the subject's postprandial lipidlevel by applying the rising index SI, the AI, the AIt, and the pulserate PR analyzed in step S503 and the subject's age to the estimationformula derived with the flowchart of FIG. 24 (step S504). The subjectis notified of the estimated postprandial lipid level by thenotification interface 147 of the electronic device 100, for example.

In this way, the electronic device 100 according to the presentembodiment uses an estimation formula derived based on the postprandialpulse wave and lipid level to estimate the subject's postprandial lipidlevel based on the subject's measured postprandial pulse wave. Theelectronic device 100 can therefore estimate the postprandial lipidlevel rapidly and in a non-invasive manner. Consequently, the electronicdevice 100 can easily estimate the subject's state of health. As anindex related to pulse wave, the AIt is less affected than the AI by thereflected wave in the pulse wave. Use of the AIt, therefore, can improvethe estimation accuracy of the subject's lipid level.

As described in the example of estimating the blood glucose level, thelipid level may also be estimated by selecting one estimation formulafrom among a plurality of estimation formulas and using the selectedestimation formula to estimate the lipid level.

In the above embodiments, examples of the electronic device 100estimating the blood glucose level and the lipid level have beendescribed, but the blood glucose level and the lipid level are notnecessarily estimated by the electronic device 100. An example of anapparatus other than the electronic device 100 estimating the bloodglucose level and the lipid level is described below.

FIG. 26 illustrates the schematic configuration of a system according toan embodiment. The system according to the embodiment illustrated inFIG. 26 includes an electronic device 100, an information processingapparatus (such as a server) 151, a mobile terminal 150, and acommunication network. As illustrated in FIG. 26, the pulse wavemeasured by the electronic device 100 is transmitted to the informationprocessing apparatus 151 over a communication network and is stored onthe information processing apparatus 151 as personal information of thesubject. On the information processing apparatus 151, the subject'sblood glucose level or lipid level is estimated by comparison with thesubject's past acquired information and with a variety of databases. Theinformation processing apparatus 151 may further prepare appropriateadvice for the subject. The information processing apparatus 151 repliesto the mobile terminal 150 in the subject's possession with estimationresults and advice. The mobile terminal 150 can construct a system toprovide notification, via the display of the mobile terminal 150, of thereceived estimation results and advice. Information from a plurality ofusers can be collected on the information processing apparatus 151 byuse of the communication function of the electronic device 100, therebyfurther improving the estimation accuracy. Furthermore, since the mobileterminal 150 is used as notification means, the electronic device 100does not require the notification interface 147 and can be furtherreduced in size. The calculation load on the controller 143 of theelectronic device 100 can also be reduced, since the subject's bloodglucose level or lipid level is estimated on the information processingapparatus 151. The subject's past acquired information can also bestored on the information processing apparatus 151, thereby reducing theload on the storage 145 of the electronic device 100. Therefore, theelectronic device 100 can be further reduced in size and complexity. Theprocessing speed for calculation also improves.

In the system according to the present embodiment, the electronic device100 and the mobile terminal 150 have been illustrated as connected overthe communication network via the information processing apparatus 151,but a system according to the present disclosure is not limited to thisconfiguration. The electronic device 100 and the mobile terminal 150 maybe connected directly over the communication network without use of theinformation processing apparatus 151.

Characteristic embodiments have been described for a complete and cleardisclosure. The appended claims, however, are not limited to the aboveembodiments and are to be construed as encompassing all of the possiblemodifications and alternate configurations that a person of ordinaryskill in the art could make within the scope of the fundamental featuresindicated in the present disclosure.

For example, in the above embodiments, the sensor 130 has been describedas being provided with the angular velocity sensor 131, but theelectronic device 100 according to the present disclosure is not limitedto this case. The sensor 130 may be provided with an optical pulse wavesensor constituted by an optical emitter and an optical detector or maybe provided with a pressure sensor. Furthermore, the electronic device100 is not limited to being worn on the wrist. It suffices for thesensor 130 to be placed on an artery, such as on the neck, ankle, thigh,ear, or the like.

For example, in the above embodiments, the explanatory variables in theregression analysis, such as PLS regression analysis or neural networkregression analysis, have been described as being age, rising index SI,AI, AIt, and pulse rate PR. The explanatory variables need not, however,include all five of these.

For example, the explanatory variables of regression analysis, such asPLS regression analysis or neural network regression analysis, need notinclude an index determined based on the acceleration pulse wave. Theindex determined based on the acceleration pulse wave is, for example,the rising index SI. For example, when the effect of the reflected waveon the pulse wave is large, as described with reference to FIGS. 15 and16, the effect of the reflected wave is also evident in the accelerationpulse wave. The estimation accuracy of the subject's blood glucose levelor lipid level may worsen when the effect of the reflected wave isevident in the acceleration pulse wave in this way. An index determinedbased on the acceleration pulse wave need not be used as an explanatoryvariable in such a case. When the acceleration pulse wave b/a is notused as an explanatory variable in PLS regression analysis or neuralnetwork regression analysis, then age, pulse rate, AI, AIt, and the likecan be appropriately selected as explanatory variables.

The explanatory variables may include variables other than these fivevariables. For example, the explanatory variables may include sex, anindex determined based on the velocity pulse wave yielded by the firstderivative of the pulse wave, or the like. The explanatory variablesmay, for example, include an index determined based on pulse. The indexbased on pulse may, for example, include the ejection time (ET) or thetime DWt from heart chamber ejection until a dicrotic wave (DW),examples of which are illustrated in FIG. 27. The explanatory variablesmay, for example, include the fasting blood glucose level (such as theblood glucose level measured by blood sampling or the blood glucoselevel measured in advance during a physical examination).

The estimation formula has been described in the above embodiments asbeing derived based on the postprandial pulse wave and the blood glucoselevel or lipid level. The estimation formula is not, however,necessarily derived based on the postprandial pulse wave and the bloodglucose level or lipid level. The estimation formula may, for example,be derived from an appropriate combination of the preprandial andpostprandial pulse waves and the preprandial and postprandial bloodglucose level or lipid level.

REFERENCE SIGNS LIST

-   100 Electronic device-   110, 210 Wearing portion-   111, 225 Opening-   120, 220 Measurement unit-   120 a Back face-   120 b Front face-   130 Sensor-   131 Angular velocity sensor-   132 Pulse pad-   133, 224 Shaft-   134 First arm-   135 Second arm-   140 Elastic body-   141 Input interface-   143 Controller-   144 Power source-   145 Storage-   146 Communication interface-   147 Notification interface-   150 Mobile terminal-   151 Information processing apparatus-   211 Base-   212 Fixing portion-   221 Body-   222 Exterior portion-   222 a Contact surface-   222 b Surface-   222 c Notch-   222 d End-   223 Connecting portion

1. An electronic device comprising: a sensor configured to acquire apulse wave of a subject; and a controller configured to analyze, basedon the pulse wave of the subject acquired by the sensor, a rate ofchange in the pulse wave at a predetermined time after a point in timeexhibiting a peak of the pulse wave and to estimate a blood glucoselevel of the subject based on the rate of change.
 2. The electronicdevice of claim 1, wherein the predetermined time is given by Δt=2L/PWV,where 2L is a round-trip distance between a heart and a reflectionpoint, the reflection point is an abdominal aortic bifurcation, and PWVis a pulse wave velocity.
 3. The electronic device of claim 1, whereinthe predetermined time is substantially 100 msec.
 4. The electronicdevice of claim 1, wherein the controller is configured to estimate theblood glucose level of the subject by applying the rate of change to anestimation formula.
 5. The electronic device of claim 4, wherein theestimation formula is derived based on a postprandial pulse wave and apostprandial blood glucose level.
 6. The electronic device of claim 4,wherein the controller is configured to estimate the blood glucose levelof the subject by using an estimation formula, among a plurality ofestimation formulas, corresponding to a content of a meal of thesubject.
 7. The electronic device of claim 6, wherein each estimationformula among the plurality of estimation formulas corresponds to acategory of the content of the meal.
 8. The electronic device of claim4, wherein the estimation formula is derived by PLS regression analysisor neural network regression analysis.
 9. The electronic device of claim4, wherein the controller is configured to estimate the blood glucoselevel of the subject by applying an index determined based on a velocitypulse wave to the estimation formula.
 10. An electronic devicecomprising: a sensor configured to acquire a pulse wave of a subject;and a controller configured to analyze, based on the pulse wave of thesubject acquired by the sensor, a rate of change in the pulse wave at apredetermined time after a point in time exhibiting a peak of the pulsewave and to estimate a lipid level of the subject based on the rate ofchange.
 11. An estimation system comprising an electronic device and aninformation processing apparatus connected communicably with each other,wherein the electronic device comprises a sensor configured to acquire apulse wave of a subject; and the information processing apparatuscomprises a controller configured to analyze, based on the pulse wave ofthe subject acquired by the sensor, a rate of change in the pulse waveat a predetermined time after a point in time exhibiting a peak of thepulse wave and to estimate a blood glucose level of the subject based onthe rate of change.
 12. An estimation system comprising an electronicdevice and an information processing apparatus connected communicablywith each other, wherein the electronic device comprises a sensorconfigured to acquire a pulse wave of a subject; and the informationprocessing apparatus comprises a controller configured to analyze, basedon the pulse wave of the subject acquired by the sensor, a rate ofchange in the pulse wave at a predetermined time after a point in timeexhibiting a peak of the pulse wave and to estimate a lipid level of thesubject based on the rate of change.
 13. An estimation method to beexecuted by an electronic device, the estimation method comprising:acquiring a pulse wave of a subject; analyzing, based on the pulse waveof the subject, a rate of change in the pulse wave at a predeterminedtime after a point in time exhibiting a peak of the pulse wave; andestimating a blood glucose level of the subject based on the rate ofchange.
 14. An estimation method to be executed by an electronic device,the estimation method comprising: acquiring a pulse wave of a subject;analyzing, based on the pulse wave of the subject, a rate of change inthe pulse wave at a predetermined time after a point in time exhibitinga peak of the pulse wave; and estimating a lipid level of the subjectbased on the rate of change.
 15. An estimation program for causing anelectronic device to execute the steps of: acquiring a pulse wave of asubject; analyzing, based on the pulse wave of the subject, a rate ofchange in the pulse wave at a predetermined time after a point in timeexhibiting a peak of the pulse wave; and estimating a blood glucoselevel of the subject based on the rate of change.
 16. An estimationprogram for causing an electronic device to execute the steps of:acquiring a pulse wave of a subject; analyzing, based on the pulse waveof the subject, a rate of change in the pulse wave at a predeterminedtime after a point in time exhibiting a peak of the pulse wave; andestimating a lipid level of the subject based on the rate of change.